Women with breast cancer, particularly those who are older and who receive adjuvant chemotherapy, are at significantly increased risk for mild cognitive impairment (MCI). Our previous research shows persistent and progressive MCI long after cancer treatment has ended. This cognitive impairment tends to involve difficulties with memory and executive function (i.e. multi-tasking, problem solving) that interfere with daily livin skills and reduce quality of life. The default mode network (DMN) is a brain circuit important for normal cognitive function. The connections between the DMN brain regions tend to naturally decrease in strength as we age. DMN functional connectivity has been demonstrated to be a highly promising neuroimaging biomarker of MCI in non-cancer populations. Disruption of DMN functional connectivity is strongly associated with conversion to dementia and has even been show to precede other biomarkers of neurodegeneration. Previous studies, including our own, show atrophy of DMN regions and damage to the white matter pathways that connect these regions following breast cancer chemotherapy. We believe that chemotherapy treatment accelerates DMN decline resulting in increased frequency of MCI following breast cancer. However, no studies to date have directly assessed the DMN or its relationship to MCI in breast cancer. The specific aims of the proposed study are therefore to 1) determine the frequency of MCI in older breast cancer subjects who receive chemotherapy, 2) identify DMN neuroimaging biomarkers in older breast cancer subjects treated with chemotherapy, and 3) develop models that predict vulnerability to MCI in this population. We will accomplish these aims by integrating longitudinal multidimensional neuropsychological assessments of cognitive function, mood and behavior with advanced, non-invasive multimodal magnetic resonance imaging techniques and APOE genotyping. We will evaluate 55 women with primary breast cancer prior to chemotherapy, one month following chemotherapy and six months following chemotherapy. We will compare the chemotherapy-treated group to 55 women with breast cancer who do not receive chemotherapy and 55 healthy females, all matched on important demographic and clinical factors. All groups will be assessed at the same time intervals. We will emphasize the assessment of memory and executive function as well as DMN functional connectivity. We will incorporate clinical, demographic, psychiatric (e.g. depression, fatigue) and genetic (e.g. APOE) factors with DMN connectivity into our predictive models of MCI. Identifying neuroimaging biomarkers underlying chemotherapy-related MCI will improve identification of individuals at highest risk for neurodegeneration and aid the development of treatments for these impairments. This is of critical importance given an aging society and the increased incidence of and vulnerability to both breast cancer and MCI.